aboutsummaryrefslogtreecommitdiff
path: root/docs/mllib-statistics.md
diff options
context:
space:
mode:
authorSean Owen <sowen@cloudera.com>2015-11-08 11:15:58 +0000
committerSean Owen <sowen@cloudera.com>2015-11-08 11:15:58 +0000
commitd981902101767b32dc83a5a639311e197f5cbcc1 (patch)
treeb0838ff14b6252b6cddf6925c7851535a40129c0 /docs/mllib-statistics.md
parent4b69a42eda3aff08eb7437c353fe2cc87ed67181 (diff)
downloadspark-d981902101767b32dc83a5a639311e197f5cbcc1.tar.gz
spark-d981902101767b32dc83a5a639311e197f5cbcc1.tar.bz2
spark-d981902101767b32dc83a5a639311e197f5cbcc1.zip
[SPARK-11476][DOCS] Incorrect function referred to in MLib Random data generation documentation
Fix Python example to use normalRDD as advertised Author: Sean Owen <sowen@cloudera.com> Closes #9529 from srowen/SPARK-11476.
Diffstat (limited to 'docs/mllib-statistics.md')
-rw-r--r--docs/mllib-statistics.md2
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/mllib-statistics.md b/docs/mllib-statistics.md
index 2c7c9ed693..ade5b0768a 100644
--- a/docs/mllib-statistics.md
+++ b/docs/mllib-statistics.md
@@ -594,7 +594,7 @@ sc = ... # SparkContext
# Generate a random double RDD that contains 1 million i.i.d. values drawn from the
# standard normal distribution `N(0, 1)`, evenly distributed in 10 partitions.
-u = RandomRDDs.uniformRDD(sc, 1000000L, 10)
+u = RandomRDDs.normalRDD(sc, 1000000L, 10)
# Apply a transform to get a random double RDD following `N(1, 4)`.
v = u.map(lambda x: 1.0 + 2.0 * x)
{% endhighlight %}